I am a Biomedical Multimodal Large Model Scientist at the International Academy of Phronesis Medicine (Guangdong), where I also serve as a Principal Investigator (PI). I founded πAI Lab to pursue autonomous scientific discovery.我现任广东智慧医学国际研究院生物医学多模态大模型科学家，担任课题组负责人（PI），并创立 πAI Lab，探索自主科学发现
My training spans clinical medicine, medical imaging, pathology, and bioinformatics. I completed my doctorate at Peking Union Medical College (Tsinghua University School of Medicine).我的学术训练涵盖临床医学、医学影像、病理学与生物信息学。我于北京协和医学院（清华大学医学院）完成博士学业
Developing AI-ready scientific infrastructure and autonomous research agents that integrate knowledge, data, models, and tools to formulate, test, and refine scientific hypotheses构建 AI-ready 科学基础设施与自主研究智能体，整合知识、数据、模型与工具，贯通科学假设的提出、检验与迭代
Developing AI virtual cell models centered on cancer-associated fibroblasts to understand how fibroblast plasticity and microenvironmental interactions shape tumor ecosystems and to predict their responses to intervention以癌症相关成纤维细胞为核心构建 AI 虚拟细胞模型，研究细胞可塑性与微环境互作如何塑造肿瘤生态，并预测其对干预的响应
PathWeaver submitted to ICLR 2027PathWeaver 投稿至 ICLR 2027
Our work explores how explicit reasoning graphs can enhance diagnostic reasoning in pathology vision-language models面向病理视觉语言模型，引入显式推理图，探索如何增强模型的诊断推理能力
OmniFigure submitted to ICLR 2027OmniFigure 投稿至 ICLR 2027
We explore a unified representation for data visualization, aiming to describe different visualization forms within a common framework聚焦数据可视化的统一表征，探索不同可视化形式之间的共通表达
Our study of fibroblast senescence appears online in Cancer Research成纤维细胞衰老与化疗耐药研究在线发表于 Cancer Research
We investigate macrophage-induced senescence in cancer-associated fibroblasts and how their senescence-associated secretory phenotype contributes to chemoresistance in colorectal cancer研究巨噬细胞诱导的癌相关成纤维细胞衰老，以及衰老相关分泌表型如何参与结直肠癌化疗耐药
Joined the International Academy of Phronesis Medicine (Guangdong)加入广东智慧医学国际研究院
Appointed as a Biomedical Multimodal Large Model Scientist, with responsibility as Principal Investigator for the multimodal biomedical AI agents research team任生物医学多模态大模型科学家，并作为课题组负责人（PI），负责生物医学多模态智能体研究
Our nasopharyngeal carcinoma study appears in Nature Cancer鼻咽癌多组学研究发表于 Nature Cancer
We use multi-omic profiling to characterize nasopharyngeal carcinoma subtypes and investigate their relationships with response to induction chemotherapy通过多组学刻画鼻咽癌分子亚型，研究不同亚型与诱导化疗应答之间的关系
Selected work on multimodal learning, cancer biology and treatment response代表研究涵盖多模态学习、肿瘤生物学与治疗响应
12,187 citations H-index 52 Google Scholar · 11 Oct 2026被引 12,187 次 H 指数 52 Google Scholar · 2026 年 10 月 11 日
AOHUPO / AOAPO / CNHUPOAOHUPO / AOAPO / CNHUPO 联合颁发
Ministry of Education · 2021, 2022, 2024, 2025教育部 · 2021、2022、2024、2025
2023–20242023–2024
2021–20222021–2022
Research collaborations in AI and biomedicine科学智能与生物医学的研究合作
